Dan Eaton’s Post

Your analytics platform was built for humans. That’s the problem. A human analyst asks one question. An AI agent asks one question…then fires off 6, 8, 12+ queries behind the scenes: Schema discovery. Metadata inspection. Candidate SQL. Validation. Follow-ups. Drill-downs. “Wait, check that again.” Now multiply that by every PM, operator, sales person, finance partner, and executive suddenly talking to data through agents. This is the future everyone is excited about. It is also the future that breaks your lakehouse/warehouse bill. Snowflake and Databricks were built for humans. But agentic analytics is a different workload. It is repetitive. It is query-heavy. It is full of joins, filters, aggregations, transformations, and validation loops. The issue is that agents turn every business user into a query-generating machine. This is why Speedata.io APUs matter. GPUs were built for AI model math. CPUs were built to be flexible. Speedata.io APUs are purpose built for SQL analytics. They accelerate the actual data operations agents depend on: scans, joins, aggregations, transformations, Spark SQL, ETL, data prep. In other words: Agents create the query explosion. APUs absorb the analytics explosion. This doesn’t mean ripping out Snowflake or Databricks. It means the next architecture will not be “one platform runs everything.” It will be: Governance in the platform. Storage in open formats. Routing at the query layer. Acceleration in purpose-built silicon. The winning data stack won’t ask, “How do we make one warehouse do everything?” It will ask: “What is the right execution path for this workload?” Some queries stay in Snowflake. Some run through Databricks. Some route to cheaper OLTP engines. And the heavy analytics/data-prep layer gets accelerated by Speedata.io APUs. That is the shift. The agent era will not be won by throwing more general-purpose compute at a workload that is becoming more specialized every week. It will be won by specialization. LLMs need GPUs. Analytics agents need Speedata.io APUs. The companies that figure this out early will make Agents feel faster. The companies that don’t will discover that Snowflake Databricks Microsoft Fabric gets prohibilitively expensive. The next bottleneck in AI is not just tokens. It is data infrastructure. And the next unlock is not another dashboard. It is analytics at the speed of silicon. #AI #DataEngineering #Analytics #Databricks #Snowflake #APU #AgenticAI #DataInfrastructure